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Strategic social media use positively influences organizational goals such as the long-term accrual of social capital, and thus social media information governance has become an increasingly important organizational objective. It is particularly important for humanitarian nongovernmental organizations (HNGOs), whose work relies on accurate and timely information regarding socially altruistic behavior (donations, volunteerism, etc.). Despite the potential of social media for increasing social capital, tensions in governing social media information across an organization's different operational levels (regional, intermediate, and national) pose a difficult challenge. Prominent governance frameworks offer little guidance, as their focus on control and incremental policymaking is largely incompatible with the processes, roles, standards, and metrics needed for managing self-governing social media. This study offers a notion of dynamic and co-evolutionary process management of multi-level organizations as a means of conceptualizing social media information governance for the accrual of organizational social capital. Based on interviews with members of HNGOs, this study reveals tensions that emerge within eight focus areas of accruing social capital in multi-level organizations, explains how dynamic process management can ease those tensions, and proposes corresponding strategy recommendations.
Does AI control or support?
(2022)
Many companies are currently investing in artificial intelligence (AI) because of its potential to increase customer satisfaction or financial performance. However, the success rates in implementing AI systems are low, partly due to technology-centric approaches that neglect work practices. This study draws on Bourdieu’s theory of practice to highlight the potential power shift related to AI in customer relationship management, based on the concepts field, capital, and habitus. Two longitudinal case studies were conducted to understand the power shift related to AI implementation. These two AI systems were designed with the objective to support employees. However, subsequently, their implementation changed the balance of power with a significant shift towards more management control, resulting in a devaluation of employees’ work practices. The paper discusses implications for theory and practice in terms of the discrepancies and power shifts following the introduction of AI systems to support customer relationship management.